Konstantinos Slavakis

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Yannis KopsinisCEO, LIBRA AI TechnologiesVerified email at libramli.ai
Georgios B. GiannakisMcKnight Presidential Chair in ECE Dept., University of MinnesotaVerified email at umn.edu
Symeon ChouvardasFrance Research Center, Huawei TechnologiesVerified email at di.uoa.gr
Masahiro YukawaKeio UniversityVerified email at elec.keio.ac.jp
Pantelis BouboulisDepartment of Informatics and Telecommunications. University of AthensVerified email at sch.gr
Leslie YingProfessor of Biomedical Engineering & Electrical Engineering, University at BuffaloVerified email at buffalo.edu
Sarah Feldt MuldoonAssociate Professor, University at Buffalo, SUNYVerified email at buffalo.edu
Gonzalo MateosUniversity of RochesterVerified email at ece.rochester.edu
Stephen McLaughlinHeriot-Watt UniversityVerified email at hw.ac.uk
David S. WackAssociate Professor, Depts. Nuclear Medicine and Biomedical Engineering, University at BuffaloVerified email at buffalo.edu
Gilad LermanUniversity of MinnesotaVerified email at umn.edu
Henry E. Baidoo-WilliamsMicrosoftVerified email at microsoft.com
Scott Grafton MDUniversity of California at Santa BarbaraVerified email at psych.ucsb.edu
Jean M. Vettel, PhDChief Scientist for Experimentation, Army Futures CommandVerified email at mail.mil
Seung-Jun KimUniversity of Maryland, Baltimore CountyVerified email at umbc.edu
Richard M. LeahyLeonard Silverman Chair in Electrical and Computer Engineering University of Southern CaliforniaVerified email at sipi.usc.edu
Geert LeusFull Professor at Delft University of Technology (TU Delft)Verified email at tudelft.nl
Zhengdao WangProfessor of Cybersecurity Engineering, George Mason UniversityVerified email at gmu.edu
Shunsuke OnoAssociate Professor, Department of Computer Science, Institute of Science TokyoVerified email at c.titech.ac.jp

Konstantinos Slavakis

Institute of Science Tokyo (ex TokyoTech), Department of Information and Communications Engineering

Verified email at ict.eng.isct.ac.jp - Homepage

Signal processing Machine learning


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Modeling and optimization for big data analytics:(statistical) learning tools for our era of data deluge K Slavakis, GB Giannakis, G Mateos IEEE Signal Processing Magazine 31 (5), 18-31, 2014	304	2014
Adaptive learning in a world of projections S Theodoridis, K Slavakis, I Yamada IEEE Signal Processing Magazine 28 (1), 97-123, 2010	261	2010
Adaptive robust distributed learning in diffusion sensor networks S Chouvardas, K Slavakis, S Theodoridis IEEE Transactions on Signal Processing 59 (10), 4692-4707, 2011	184	2011
Online Sparse System Identification and Signal Reconstruction Using Projections Onto Weighted Balls Y Kopsinis, K Slavakis, S Theodoridis IEEE Transactions on Signal Processing 59 (3), 936-952, 2010	184	2010
An efficient robust adaptive filtering algorithm based on parallel subgradient projection techniques I Yamada, K Slavakis, K Yamada IEEE Transactions on Signal Processing 50 (5), 1091-1101, 2002	167	2002
Online kernel-based classification using adaptive projection algorithms K Slavakis, S Theodoridis, I Yamada IEEE Transactions on Signal Processing 56 (7), 2781-2796, 2008	133	2008
Robust wideband beamforming by the hybrid steepest descent method K Slavakis, I Yamada IEEE Transactions on Signal Processing 55 (9), 4511-4522, 2007	112	2007
A sparsity promoting adaptive algorithm for distributed learning S Chouvardas, K Slavakis, Y Kopsinis, S Theodoridis IEEE Transactions on Signal Processing 60 (10), 5412-5425, 2012	106	2012
The adaptive projected subgradient method over the fixed point set of strongly attracting nonexpansive mappings K Slavakis, I Yamada, N Ogura Numerical functional analysis and optimization 27 (7-8), 905-930, 2006	99	2006
Adaptive constrained learning in reproducing kernel Hilbert spaces: The robust beamforming case K Slavakis, S Theodoridis, I Yamada IEEE Transactions on Signal Processing 57 (12), 4744-4764, 2009	86	2009
Adaptive kernel-based image denoising employing semi-parametric regularization P Bouboulis, K Slavakis, S Theodoridis IEEE Transactions on Image Processing 19 (6), 1465-1479, 2010	80	2010
Adaptive learning in complex reproducing kernel Hilbert spaces employing Wirtinger's subgradients P Bouboulis, K Slavakis, S Theodoridis IEEE transactions on neural networks and learning systems 23 (3), 425-438, 2012	72	2012
Sliding window generalized kernel affine projection algorithm using projection mappings K Slavakis, S Theodoridis EURASIP Journal on Advances in Signal Processing 2008, 1-16, 2008	72	2008
Online learning in reproducing kernel Hilbert spaces K Slavakis, P Bouboulis, S Theodoridis Academic Press Library in Signal Processing 1, 883-987, 2014	70	2014
Adaptive parallel quadratic-metric projection algorithms M Yukawa, K Slavakis, I Yamada IEEE transactions on audio, speech, and language processing 15 (5), 1665-1680, 2007	68	2007
Trading off complexity with communication costs in distributed adaptive learning via Krylov subspaces for dimensionality reduction S Chouvardas, K Slavakis, S Theodoridis IEEE Journal of Selected Topics in Signal Processing 7 (2), 257-273, 2013	59	2013
Sparsity-aware learning and compressed sensing: An overview S Theodoridis, Y Kopsinis, K Slavakis Academic Press Library in Signal Processing 1, 1271-1377, 2014	58	2014
Stochastic approximation vis-a-vis online learning for big data analytics [lecture notes] K Slavakis, SJ Kim, G Mateos, GB Giannakis IEEE Signal Processing Magazine 31 (6), 124-129, 2014	57	2014
Multi-kernel based nonlinear models for connectivity identification of brain networks GV Karanikolas, GB Giannakis, K Slavakis, RM Leahy 2016 IEEE International Conference on Acoustics, Speech and Signal …, 2016	56	2016
Adaptive multiregression in reproducing kernel hilbert spaces: The multiaccess mimo channel case K Slavakis, P Bouboulis, S Theodoridis IEEE Transactions on Neural Networks and Learning Systems 23 (2), 260-276, 2011	47	2011

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